arXiv:2607. 28631v1 Announce Type: new Abstract: AI Scientist systems capable of autonomous research have the potential to significantly accelerate scientific discovery.
By Vaibhava Lakshmi Ravideshik, Mayank Kejriwal
SciDocBench is a workflow-centered benchmark for scientific document understanding that includes 124 expert-authored questions across seven capability groups and 19 subtasks in five scientific domains. Each question is evaluated under four conditions—English or Chinese, all-images-first or interleaved document representations—resulting in 496 evaluation instances. The benchmark is paired with SciDocIR, a typed evidence-graph representation, and SciDocDataset, a collection of 15K fine-tuning and 8K reinforcement-learning samples, forming an evaluation-to-training framework for scientific-document assistants.
By Shenxi Wu, Yuhong Liu, Haosong Zhang, Tongjin Zou, Yanxun Zhang, Gaochang Chen, Dun Liang, Jiaqi Wang, Zhecan James Wang, Yuhang Zang, Dahua Lin
arXiv:2606. 11337v1 Announce Type: new Abstract: Scientific AI agents increasingly retrieve evidence, reason across sources, and synthesize conclusions used in consequential decisions.
By Hayoung Jung, Pedro Viana Diniz, Jos\'e Reinaldo Corr\^ea Roveda, Abner Fernandes da Silva, Haeun Jung, Enoch Tsai, Aleksandra Korolova, Manoel Horta Ribeiro
PaperDoctor is an agent framework that provides evidence‑grounded, actionable feedback for scientific papers before submission. It evaluates writing, layout, references, code, theory, prior work, and experiments through a three‑layer hierarchical system, linking each critique to specific evidence and revision suggestions. The system selectively rebuilds and reruns experiments to uncover reproducibility gaps, and an interactive interface lets authors explore findings tied to their manuscript.
By Kevin Qinghong Lin, Siyuan Hu, Pan Lu, Yu Chen, Yanzhe Chen, Owen Queen, Yupeng Chen, Jialin Yu, Junchi Yu, Zifeng Ding, Yuanfeng Ji, Sheng Liu, Jindong Gu, Linjie Li, Mike Zheng Shou, Philip Torr, James Zou
arXiv:2606. 13020v1 Announce Type: new Abstract: Three paradigmatic forms of inference recur across scientific reasoning: deduction, induction, and causal abduction.
By Pierre Beckmann, Marco Valentino, Andre Freitas
arXiv:2607. 05456v1 Announce Type: new Abstract: While recent advances in large language models have enabled end-to-end automated manuscript generation, existing systems suffer from three critical deficiencies: (i) generated claims are not deterministically grounded in verifiable literature, (ii) experimental results are frequently fabricated rather than executed, and (iii) there exists no standardized, multi-dimensional framework to assess whether AI-generated manuscripts meet the quality and rigor required for real-world publication.
By Ramsha Kamran, Maheera Amjad, Zartasha Mustansar, Arsalan Shaukat, Salma Sherbaz, Muhammad U. S. Khan